The Bead-based Suspension Array In Detection Of Common Pathogens In Lower Respiratory Tract Infection Patients And Establish The Prediction Model In Community Acquired Pneumonia Pathogens

Part 1 The clinical application research on bead-based suspension array in cases of acute respiratory tract infectionsobjective:In recent years as the outbreak of SARS epidemic,lower respiratory tract infections etiology is more and more complex,early diagnosis is very important to prognosis of pathogen,bead-based suspension array is developing rapidly in recent years can be used for high-throughput,rapid screening of a variety of pathogenic detection technology,this study intends to use research of liquid chip testing technology to test the lower respiratory tract in clinical specimens,and compared with the gold standard in order to further verify the clinical value of detectionMethods:Collected in March 2012 to March 2016 in fujian province,multi center study(including Fujian provincial hospital,putian institute affiliated hospital,sanming first hospital,wuyi city hospital four hospitals)of respiratory department,819 patients with acute lower respiratory infections,collected 819 sputum samples,use the bead-based suspension array at the same Time for 6 kinds of bacteria(Staphylococcus aureu;Acinetobacter baumannii;Klebsiella Pneumoniae;Pseudomonas aeruginosa;Streptococcus pneumonia;Stenotrophomonas maltophilia)and 12 kinds of virus(Human Cytomegalovirus;Influenza A virus;Human Parainfluenza Virus 1;Human Parainfluenza Virus 2;Human Parainfluenza Virus 3;Respiratory Syncytial Virus;Human metapneumovirus;Human bocavirus;Severe Acute Respiratory Syndrome;Influenza A virus subtype N1;Influenza A virus subtype H5;Adenovirus)detection,and bacteria detection with traditional bacterial culture method as the gold standard,virus detection in Real Time fluorescence quantitative PCR(Real-Time PCR)as the gold standard.Analysis the specificity,sensitivity,positive predictive value and negative predictive value and accuracy of bead-based suspension array,and concludes that the technology in the clinical application value.Results:The bead-based suspension array in the 7～8 hours of 96 specimens of 18 kinds of pathogen detection.Testing results of 819 specimens of respiratory pathogens positive rate was 62.27%(510/819),bacterial positive rate of pathogenic bacteria was 43.22%(354/819),the virus positive rate was 33.21%(272/819).One of the most common pathogen is:staphylococcus aureus,streptococcus pneumoniae,klebsiella pneumoniae,acinetobacter baumannii,pseudomonas aeruginosa,Stenotrophomonas maltophilia,the bead-based suspension array positive rate were 5.13%,13.19%,13.36%,5.86%,15.87%,5.49%,significantly higher than the traditional sputum culture method(sputum specimens were respectively 2.08%,0.73%,1.83%,2.08%,2.81%,0.61%,P<0.05).The sensitivity of the bead-based suspension array in detecting human cytomegalo virus,adenovirus,Human Parainfluenza Virus 1;Human Parainfluenza Virus 2;Human Parainfluenza Virus 3,respiratory syncytial virus,Severe Acute Respiratory Syndrome,influenza A virus,influenza A virus subtype N1;Influenza A virus subtype H5,Human metapneumovirus,Human bocavirus was 65.31%,26.67%,12.5%,100%,57.14%,42.00%,N/A,65.63%,N/A,50%,33.33%,100%.Specific degrees are divided into 93.20%,99.75%,99.38%,99.51%,99.50%,99.63%,N/A,91.03%,99.15%,99.76%,99.75%,99.63%.The bead-based suspension array to detect bacteria positive predictive value of 11.37%(8.64%～14.61%),negative predictive value of 99.32%(99.04%～99.54%),the accuracy of 90.97%(90.14%～91.76%).Detection of virus positive predictive value of 54.6%(48.93%～60.19%),negative predictive value of 98.8%(98.56%～99.01%),the accuracy of 97.38%(97.05%～97.69%).Conclusion:Our research and development of bead-based suspension array has the characteristics of high flux,rapid detection,this method has high sensitivity and specific degrees,is expected to become a new method of clinical respiratory pathogen detection,is worth popularizing in clinical applicationPart 2 The study on common pathogens in hospitalized patients with lower respiratory tract infection in Fujian ProvinceObjective:This study aimed to detect the pathogens in patients with lower respiratory tract infection(LRTI)using a bead-based suspension array and analyze the epidemiological and clinical characteristics of the patients in Fujian Province,thereby guiding the clinical treatment.Methods:Sputum were collected from 819 hospitalized patients diagnosed with LRTI from the Department of Respiratory Medicine of the four hospitals(Fujian provincial hospital,putian institute affiliated hospital,sanming first hospital,wuyi city hospital four hospitals)in Fujian Province from March 2012 to March 2016.The pathogens were detected using a bead-based suspension array and the data were statistically analyzed in combination with the clinical information.Results:The first three bacterial infection in hospitalized patients with lower respiratory tract infections were PA,SP,KP,three for virus were Flu-A,HCMV,AD.Analysis of prevalence of the top three diseases,502 cases of patients with community-acquired pneumonia(CAP)to detect the bacterial top three for the PA(14.14%),SP(13.14%),KP(11.55%),the virus top two for Flu-A(17.13%)and HCMV(12.95%).AE-COPD 204 cases in which detect the three bacteria for SP(16.18%),PA(12.25%),KP(11.27%),the virus top two for Flu-A(17.65%)and HCMV(15.69%),AEB of 113 patients in which detect the three bacteria for PA(30.09%),KP(10.62%),SP(7.96%),the virus top two for Flu-A(21.24%)and HCMV(14.16%).819 patients with lower respiratory tract can be divided into four groups:113 cases of mixed infection with bacteria and viruses,241 cases of bacterial infection,159 cases of virus infection,the clinical data of 306 cases did not check out compare the clinic date of the four groups.In the gender distribution,basic diseases,presence of breathing and extrapulmonary complications etc,there was no statistically significant difference(P>0.05);long heating time and are more likely to happen pleural effusion in mixed infection group,and copare the rest of the three groups was statistically significant difference(P<0.05).In terms of imaging findings,a large patch of shade of mixed infection groups more prone to pleural effusion in lung imaging is more large patch density increased,bacterial infection group and simplex virus infection is given priority to with the increase in platelet density,statistically significant difference between the four groups(P<0.05).Bacteria and viruses mixed infection group of lower respiratory tract infection in the course of the disease(period)of white blood cells,neutrophils ratio and CRP level average significantly higher than the other three groups,the differences were statistically significant(P<0.05).Conclusion:The common pathogenic bacteria in lower respiratory tract infection pathogens in fujian province were pseudomonas aeruginosa,streptococcus pneumoniae,klebsiella pneumonia bacillus,virus for Flu-A,human cytomegalo virus were given priority,through the analysis of the epidemiology and clinical characteristics of etiology can guide clinical drug use.Part 3 Hospitalized patients with community acquired pneumonia pathogens to build up the prediction modelObjective:Screening from 819 patients with lower respiratory tract infections to 502 hospitalized patients with community-acquired pneumonia,based on statistical methods and according to the clinical information,the virus/bacteria infection prediction model was established,help early judgment of community-acquired hospitalized patients pneumonia pathogen and early targeted antiviral treatment.Methods:According to the results of pathogen detection,502 cases of community-acquired pneumonia were divided into bacterial infection group(I)in 138 cases,simple viral infection group(II)in 104 cases,mixed infection group(III)in 64 cases and pathogen detection negative group(IV)in 196 cases.Collect patients’ basic information and medical history and medication history,and the patient’s symptoms and signs,laboratory examination and imaging examination data,etc.To normality test of quantitative data,if meet the normal distribution,mean+standard deviation(X±S)is used to describe the central tendency and discrete trend,if not meet the normal distribution,taking the median and interquartile spacing;The qualitative data expressed in percentage(%).Multiple sets of the comparison between the normal data using analysis of variance(ANOVA),The SNK method is used to pairwise comparison;Use the Kruskal-Wallis H testing in Multiple sets of quantitative data of non-normal comparison,Use the Nemenyi method in pairwise comparison;The comparison of multiple sets of qualitative data using chi-square test.P<0.05 show difference was statistically significant.In forecasting model analysis,multivariate logistic regression analysis based on screening of related variables with Single factor logistic regression analysis,set up probability prediction equation,and use the nomogram prediction equation for visual figure.Results:We will use group I and IV group patients to establishe bacterial infection prediction model.By single factor logistic regression analysis results,use statistically significant factors in multiariable logistic regression analysis.it is concluded independent factors equation:.we will use group III and IV group patients to establishe Virus infection model.By single factor logistic regression analysis results,use statistically significant factors in multiariable logistic regression analysis.it is concluded that the equation:.P(y=1)e=exp(0.582+1.235×咳痰+0.885×高血压+0.677×CRUB-65)/1+exp(-0.582+1.235×咳痰+0.885×高血压+0.677×CRUB-65).we will use group III and IV group patients to establishe Virus infection model.By single factor logistic regression analysis results,use statistically significant factors in multiariable logistic regression analysis.it is concluded that the equation:P(y=1)=exp(-0.796+1.603×免疫抑制治疗0.904×CRUB-65)/1+exp(-0.796+1.603×免疫抑制治疗0.904CRUB-65).At the same time use the nomogram of the above three prediction equations are visual figure.Conclusion:This study CAP pathogens prediction model is established,and found that by the probability forecast equations or nomogram help predict bacteria or virus infection.Help to clinical early diagnosis,bacteria or virus infection for early targeted therapy.Part 4 Anti-pneumonia role and the underlying mechanisms of traditional Chinese medicine brucea javanica oilObjective:Brucea javanica oil(Brucea javanica oil,BJO),a traditional Chinese medicine extracted from the nuts or seeds of brucea javanica,exhibits inhibitory effects on lung cancer,gastritis and colitis.However,whether BJO also has anti-pneumonia effect remains unclear.The aim of this study is to explore the anti-pneumonia role of BJO and the underlying molecular mechanisms.Methods:Lipopolysaccharide(lipopolysaccharides,LPS)was used to stimulate RAW264.7 cells to establish inflammation cell model.Four cell groups were involved,including:control group,LPS-treated group,BJO(5 μmol/L or 10 μmol/L)plus LPS-treated groups.For BJO plus LPS-treated groups,cells were pre-treated wth BJO for 2 h,and then LPS were added(final concentration 1 μg/mL)to stimulate cells.ELISA method was used to detect the concentration of pneumonia-related inflammatory factor TNF-a,IL-1β,IL-6 and IL-8 in the cell culture supernatant of RAW264.7 cells.Real-time PCR method were used to analyze the mRNA expression level of TNF-a,IL-1β,IL-6 and IL-8 in RAW264.7 cells And the phosphorylation levels of IκB and NF-κB/p65 proteins in RAW264.7 cells were measured by western blot analysisResults:LPS could stimulate the expression and secretion of pneumonia-related inflammatory factor TNF-a,IL-1β,IL-6 and IL-8 in RAW264.7 cells;however,BJO co-treatment dose-dependently inhibited the expression and secretion of these inflammatory factors induced by LPS.Further studies in RAW264.7 cells found that LPS elevated the phosphorylation levels of IκB and NF-κB/p65 proteins,two key molecules of NF-κB signaling pathway,while BJO co-treatment could significantly weaken the effects of LPS on the phosphorylation levels of IκB and NF-KB/p65 proteinsConclusion:Our results suggested that BJO inhibits the expression and secretion of pneumonia-related inflammatory factors through suppressing the NF-κB signaling pathway in macrophages,and thus plays anti-pneumonia roles.This study may provide a theoretical basis for BJO emulsion to be an adjunctive drug for pneumonia treatment.